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Ketamine and olanzapine alter behaviour and prefrontal-cortex BDNF differentially in male and female rats
Maturity related metabolomic analysis of Balanites aegyptiaca fruits with in vitro and in silico cytotoxicity evaluation
Abstract Balanites aegyptiaca (L.) Delile, a medicinal tree, produces an edible fruit widely recognized in traditional medicine for its antidiabetic and liver-enhancing properties. This study investigated the metabolic changes occurring during fruit maturation using integrated nuclear magnetic resonance (NMR) metabolomics approaches, including 1D 1H (proton), 2D heteronuclear single quantum coherence (HSQC), and 2D J-resolved NMR spectroscopy. A total of forty-five metabolites were identified and quantified, with key metabolites characterizing each maturation stage. Metabolic profiling indicated that immature fruits were characterized by elevated concentrations of amino acids, alkaloids, and organic acids, while mature fruits predominantly accumulated monosaccharides. Chemometric analyses and hierarchical clustering confirmed a significant metabolic differentiation between immature and mature fruit stages. Pathway analysis identified significant alterations predominantly in starch–sucrose metabolism, pyruvate metabolism, and the citrate cycle during maturation. Cytotoxic evaluation revealed that polar extracts from immature fruits exhibited superior cytotoxic activity against hepatocellular carcinoma cells (IC50 = 117.7 µg/mL) compared to mature fruit extracts (IC50 = 270.4 µg/mL). Molecular docking analysis further demonstrated that metabolites upregulated in immature fruits, like theophylline, showed a strong binding affinity (− 5.317 kcal/mol) to the anti-apoptotic protein BCL-2, suggesting their potential role in apoptosis regulation. This study provides insights into the metabolic dynamics during Balanites aegyptiaca fruit maturation, highlighting the superior therapeutic potential and significant cytotoxic activity of immature fruits compared to traditionally utilized mature fruits.
Comparative analysis of deep learning and traditional methods for IoT botnet detection using a multi-model framework across diverse datasets
Average quantum dynamics of closed systems over stochastic Hamiltonians
Abstract We develop a formally exact master equation to describe the evolution of the average density matrix of a closed quantum system driven by a stochastic Hamiltonian. The average over stochastic processes generally results in decoherence effects in closed system dynamics, in addition to the unitary evolution. We then show that, for an important class of problems in which the Hamiltonian is proportional to a Gaussian random process, the 2nd-order master equation yields exact dynamics. The general formalism is applied to study the examples of a two-level system, two atoms in a stochastic magnetic field and the heating of a trapped ion, where we find phenomena such as decoherence-induced disentanglement.
Proteomics on choroidal neovascularization based on itraq and the protective effect of TAB1 in CNV
The correlation of HLA-A in Thai EGFR-mutated advanced non-small cell lung cancer, outcome, and tumor microenvironment
Intestinal bacteria translocation promotes β-cell dysfunction in DIO mice
Developing a hybrid machine learning model to predict treatment time duration as a workflow regulation tool in public and private dental clinics
Neural correlates of span capacity during visual discrimination under varying cognitive demands
High fat diet enhances catalase loading into adipose tissue derived extracellular vesicles with limited effect on oxidative stress
Obesity impact on leukocyte telomere shortening and immune aging assessed by Mendelian randomization and transcriptomics analysis
Abstract Obesity and aging are key research topics in contemporary biomedical science. While studies have explored the effects of obesity on various health indicators, the precise mechanisms through which obesity may affect leukocyte telomere length (LTL)-and whether this impact contributes to accelerated immune cell senescence-remain unclear and warrant further investigation. In this study, we employed single nucleotide polymorphisms (SNPs) associated with four obesity indices—body mass index (BMI), body fat percentage (BFP), waist circumference (WC), and waist-hip ratio (WHR)—as instrumental variables (IVs) to assess the causal relationship between these indices and LTL through Mendelian randomization (MR) analysis. Additionally, we analyzed transcriptome sequencing data from peripheral blood mononuclear cells (PBMCs) across three groups: lean individuals, individuals with obesity before undergoing bariatric surgery, and individuals with obesity after surgery, and focus on the expression changes of cellular senescence and telomere dynamics related genes in PBMCs of individuals with obesity before and after weight loss intervention. The results showed a negative causal relationship between BMI (B=-0.04, P < 0.0001), BFP (B=-0.06, P < 0.0001) and LTL without being impacted by lipid profiles and T2D. The negative causal relationship between WC (B=-0.04, P < 0.0001) and LTL may be dependent on lipid levels, but not on T2D. WHR had no significant causal relationship (P > 0.05). Transcriptomic analysis further revealed that individuals with obesity had higher expression of cellular senescence-related genes such as ID2, LMNA, and TENT4B in PBMCs compared to lean individuals, with expression levels of these genes significantly decreasing after bariatric surgery. These findings underscore the detrimental impact of obesity on telomere attrition and immune cell senescence, highlighting the potential benefits of obesity management for slowing the biological process of cellular and immune aging.
Asymptotic consensus of hybrid multi-agent systems considering network attacks
Abstract This paper focuses on the problem of active defense and achieving asymptotic consensus control in hybrid multi-agent systems under network attacks. Considering the influence of Byzantine nodes, on the basis of the theory of mimic defense, a deep dynamic heterogeneous redundancy architecture for hybrid multi-agent systems is established. Drawing on the Lyapunov asymptotic stability theory, a hybrid multi-agent asymptotic consensus is proposed. Furthermore, a hybrid multi-agent progressive consensus clustering review strategy is suggested. Via Lyapunov asymptotic stability theory, the sufficient and necessary conditions for achieving the asymptotic consensus of hybrid multi-agent systems on the basis of a hybrid clustering review strategy are proven. The strategy’s extended application method in asymptotic proportional consensus, enabling multi-agent systems with various target tasks to achieve asymptotic proportional consensus, is presented. The theoretical results are validated through numerical examples.